clc;clear;clearvars;
% 随机生成5个数据
num_initial = 5;
num_vari = 5;
% 搜索区间
upper_bound = 5.12;
lower_bound = -5.12;
iter = 10000;
w = 0.1;
% 随机生成5个数据,并获得其评估值
sample_x = lhsdesign(num_initial, num_vari).*(upper_bound - lower_bound) + lower_bound.*ones(num_initial, num_vari);
sample_y = F1(sample_x);
Fmin = zeros(30, 1);
W = zeros(30, 1);
k = 1;
while w < 3
    % 初始化一些参数
    pbestx = sample_x;
    pbesty = sample_y;
    % 当前位置信息presentx
    presentx = lhsdesign(num_initial, num_vari).*(upper_bound - lower_bound) + lower_bound.*ones(num_initial, num_vari);
    vx = sample_x;
    [fmin, gbest] = min(pbesty);
    for i = 1 : iter
        r = rand(num_initial, num_vari);
        % pso更新下一步的位置,这里可以设置一下超过搜索范围的就设置为边界
        vx = w.*vx + 2 * r .* (pbestx - presentx) + 2 * r .* (pbestx(gbest, :) - presentx);
        vx(vx > upper_bound) = upper_bound;
        vx(vx < lower_bound) = lower_bound;
        presentx = presentx + vx;
        presentx(presentx > upper_bound) = upper_bound;
        presentx(presentx < lower_bound) = lower_bound;
        presenty = F1(presentx);
        % 更新每个单独个体最佳位置
        pbestx(presenty < pbesty, :) = presentx(presenty < pbesty, :);
        pbesty = F1(pbestx);
        % 更新所有个体最佳位置
        [fmin, gbest] = min(pbesty);
        % fprintf("iter %d fmin: %.4f\n", i, fmin);
    end
    fprintf("w %f fmin: %.4f\n", w, fmin);
    Fmin(k, 1) = fmin;
    k = k +1;
    w = w + 0.1;
end
plot(Fmin);